WANG Da-dong, YANG De-bin, and XU Jin-wu, RECOGNITION OF WEAR PARTICLES IN LUBRICATING OIL USING LVQ NEURAL CLASSIFIER, J. Univ. Sci. Technol. Beijing, 3(1996), No. 1, pp. 26-30.
Cite this article as:
WANG Da-dong, YANG De-bin, and XU Jin-wu, RECOGNITION OF WEAR PARTICLES IN LUBRICATING OIL USING LVQ NEURAL CLASSIFIER, J. Univ. Sci. Technol. Beijing, 3(1996), No. 1, pp. 26-30.
WANG Da-dong, YANG De-bin, and XU Jin-wu, RECOGNITION OF WEAR PARTICLES IN LUBRICATING OIL USING LVQ NEURAL CLASSIFIER, J. Univ. Sci. Technol. Beijing, 3(1996), No. 1, pp. 26-30.
Citation:
WANG Da-dong, YANG De-bin, and XU Jin-wu, RECOGNITION OF WEAR PARTICLES IN LUBRICATING OIL USING LVQ NEURAL CLASSIFIER, J. Univ. Sci. Technol. Beijing, 3(1996), No. 1, pp. 26-30.
A technique for wear particle identification using computer vision system is described. The computer vision system employs LVQ Neural Networks as classifier to recognize the surface texture of wear particles in lubricating oil and determine the conditions of machines. The recognition process includes four stages:(1) capturing image from ferrographies containing wear particles;(2) digitising the image and extracting features;(3) learning the training data selected from the feature data set;(4) identifying the wear particles and generating the result report of machine condition classification. To verify the technique proposed here, the recognition results of several typical classes of wear particles generated at the sliding and rolling surfaces in a diesel engine are presented.